def test_neofox(self):
"""
This test is equivalent to the command line call:
neofox --candidate-file /projects/SUMMIT/WP1.2/neofox/development/Pt29.sequences4testing.txt --patient-id Pt29
--patients-data ../resources/patient.pt29.csv
NOTE: we will need to check the output when the calculation of resuls and printing to stdout have been decoupled
"""
output_file = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_{:%Y%m%d%H%M%S}_neoantigen_candidates_annotated.tsv"
.format(datetime.now()),
)
output_file_neoantigens = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_{:%Y%m%d%H%M%S}.neoantigens.tsv".format(
datetime.now()),
)
output_json_neoantigens = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_{:%Y%m%d%H%M%S}.neoantigen_candidates.json".
format(datetime.now()),
)
annotations = NeoFox(
neoantigens=self.neoantigens,
patient_id=self.patient_id,
patients=self.patients,
num_cpus=4,
).get_annotations()
annotation_names = [
a.name for n in annotations
for a in n.neofox_annotations.annotations
]
# check it does contain any of the MixMHCpred annotations
self.assertIn("MixMHC2pred_best_peptide", annotation_names)
self.assertIn("MixMHC2pred_best_rank", annotation_names)
self.assertIn("MixMHC2pred_best_allele", annotation_names)
self.assertIn("MixMHCpred_best_peptide", annotation_names)
self.assertIn("MixMHCpred_best_score", annotation_names)
self.assertIn("MixMHCpred_best_rank", annotation_names)
self.assertIn("MixMHCpred_best_allele", annotation_names)
# checks it does have some of the NetMHCpan annotations
self.assertIn("Best_affinity_MHCI_9mer_position_mutation",
annotation_names)
self.assertIn("Best_rank_MHCII_score", annotation_names)
# writes output
ModelConverter.annotations2table(neoantigens=annotations).to_csv(
output_file, sep="\t", index=False)
ModelConverter._objects2dataframe(annotations).to_csv(
output_file_neoantigens, sep="\t", index=False)
with open(output_json_neoantigens, "wb") as f:
f.write(json.dumps(ModelConverter.objects2json(annotations)))
# regression test
self._regression_test_on_output_file(new_file=output_file)
def test_neomouse(self):
output_file = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_mouse_{:%Y%m%d%H%M%S}_neoantigen_candidates_annotated.tsv"
.format(datetime.now()),
)
output_file_neoantigens = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_mouse_{:%Y%m%d%H%M%S}.neoantigens.tsv".format(
datetime.now()),
)
output_json_neoantigens = pkg_resources.resource_filename(
neofox.tests.__name__,
"resources/output_mouse_{:%Y%m%d%H%M%S}.neoantigen_candidates.json"
.format(datetime.now()),
)
annotations = NeoFox(
neoantigens=self.neoantigens_mouse,
patient_id=self.patient_id,
patients=self.patients_mouse,
num_cpus=4,
reference_folder=self.references_mouse).get_annotations()
annotation_names = [
a.name for n in annotations
for a in n.neofox_annotations.annotations
]
# checks it does have some of the NetMHCpan annotations
self.assertIn("Best_affinity_MHCI_9mer_position_mutation",
annotation_names)
self.assertIn("Best_rank_MHCII_score", annotation_names)
# writes output
ModelConverter.annotations2table(neoantigens=annotations).to_csv(
output_file, sep="\t", index=False)
ModelConverter._objects2dataframe(annotations).to_csv(
output_file_neoantigens, sep="\t", index=False)
with open(output_json_neoantigens, "wb") as f:
f.write(json.dumps(ModelConverter.objects2json(annotations)))
# regression test
self._regression_test_on_output_file(
new_file=output_file,
previous_filename="resources/output_previous_mouse.txt")
def _write_results(neoantigens, output_folder, output_prefix, with_json,
with_table):
# NOTE: this import here is a compromise solution so the help of the command line responds faster
from neofox.model.conversion import ModelConverter
# writes the output
if with_table:
ModelConverter.annotations2table(neoantigens).to_csv(
os.path.join(
output_folder,
"{}_neoantigen_candidates_annotated.tsv".format(output_prefix),
),
sep="\t",
index=False,
)
if with_json:
output_features = os.path.join(
output_folder,
"{}_neoantigen_candidates_annotated.json".format(output_prefix))
with open(output_features, "wb") as f:
f.write(json.dumps(ModelConverter.objects2json(neoantigens)))